\chapter{Existing System for Administrating Heavy Peptides}
\label{chap:existingSystem}

Administrating PROBE's processes around heavy peptides and the storage of data regarding these heavy peptides, is the main objective of this thesis. Use of heavy peptides in SRM analysis was introduced in Section~\ref{sec:srm}. PROBE quantifies proteins through SRM analysis, and heavy peptides that uniquely identify these proteins are thus needed in experiments. This chapter describes the workflow PROBE's researchers use when handling heavy peptides, and how they organize and store the data pertaining to these peptides. 

The key tasks performed when handling heavy peptides can be divided into to the following categories:

\begin{itemize}
	\item Order heavy peptides
	\begin{itemize}
	  \item Determine which peptides to order
	  \item Quality control
	\end{itemize}
	\item Organize heavy peptide samples
	\item Organize data about heavy peptides
	\item Store data about heavy peptides
\end{itemize}

The workflow at PROBE for administrating heavy peptides has not been defined by a standard template. When ordering (heavy) peptides for use in SRM analysis experiments from external companies, each company requires the order to be on a unique standard format specific for that company before the order is submitted to them. PROBE is by default adhering to all of these different format requirements from external companies, but an internal standard for storing heavy peptide data has not yet been defined at PROBE.

\section{Order heavy peptides}
\label{sec:peptideOrders}

When ordering peptides all the work has been done manually. Building a new heavy peptide order has been a time-consuming task, taking as much as 24 working hours, or approximately three work days, to complete for one person.

\subsection{Determine which peptides to order}

Determining which peptides to potentially include in an order is the first step in the order process. The researcher responsible for creating and submitting the order performs a process of elimination on the basis of an analysis of experiments performed on proteins in the laboratory to determine which peptides to order.

After an experiment, a number of proteins are discovered as potential biomarkers. These proteins are normally identified in the experiment by two (or more) peptides, and these peptides are usually included in the order. However, from time to time some of these peptides are not suitable for SRM analysis. If a peptide is not suitable for SRM analysis, or there are other reasons why the peptide is unsuitable for use in an upcoming experiment, software such as Skyline\footnote{Shortened URL: http://bit.ly/HN3tGs} is used to uncover alternative peptides for the given protein.

Theoretical analysis of proteins is also performed. Occasionally the researchers will order peptides from proteins that look promising in theory, without having any background information based on experiments for that particular protein. When this is the case, Skyline is used to identify potential peptides from the protein to include in the upcoming order.

\subsection{Quality control}

As soon as the researcher has compiled a list of which peptides to include in the upcoming order, each peptide has to be checked to make sure that it only maps to one protein. This is done by performing a BLAST search on each peptide, utilizing the BLAST tool\footnote{http://www.uniprot.org/?tab=blast} at UniProt's web pages. If only a handful of peptides need to be BLAST-ed this is not an unreasonably inefficient way of acquiring the desired information, but when dealing with numbers in their twenties to thirties and higher this becomes a cumbersome process that can be automatized, saving significant amounts of time.

\section{Organizing samples}

The first thing that is done when peptide orders are received at PROBE is to divide the samples into aliquots (smaller portions of the total sample). Samples are divided into aliquots so that the same sample may be used in several different experiments by only using a portion of the total sample. Usually 10 stock aliquots are created and stored in a freezer with a temperature of $-80\,^{\circ}\mathrm{C}$. One of the stock aliquots is diluted into solvents ready for use, which are stored in a different freezer with a temperature of $-20\,^{\circ}\mathrm{C}$. In general, 10 aliquots are created when diluting the stock aliquots into solvents used in experiments.

In the freezers, peptides are stored in boxes labeled with the sales order code of the order, and a plate position (A1-A10 and so on). Peptide tubes are labeled with the sales order code, plate position and which solvent they are diluted in (typically 10\% acetonitrile and 0,1\% formic acid).

\section{Organization and storage of heavy peptide data}
\label{sec:existingStorage}

When the heavy peptides ordered are returned to PROBE they are accompanied by a lot of information about said peptides; including amongst others the amount delivered of each peptide, the peptide's molecular weight, and which well on the delivered plate(s) each peptide is positioned in (plate position). This information is relayed to PROBE in a higly variable manner. Some times the orders are accompanied by a CD with files containing the necessary information, while the files for other orders are e-mailed back to PROBE as an attachment. This discrepancy in delivery methods causes trouble when trying to organize the data about the orders and peptides.

Because of the varying delivery methods used to provide PROBE with the information needed about the heavy peptides ordered, it has been a challenge to organize all the data and make it easily available for all their reserchers. Packing slips, invoices, and CDs, all of which may contain variable amounts and types of information about the order that they accompany, are hard to organize and extract information from due to the many variations they come in. Without a central way of storing the data, information may become fragmented quickly as the different types of information may be stored in different locations and manners. In lieu of a central storage scheme with all the data stored on the same format, a temporary solution was set up to provide a central resource for storing data. By using Google Drive (previously Google Documents), a solution enabling collaboration between multiple users on the same document hosted in the cloud, PROBE managed to provide all their researchers with a collective resource, a spreadsheet, for storing, organizing, and retrieving data about heavy peptides. Although such a solution is not considered optimal for these purposes, it does provide a good foundation to expand upon when building a new system. A common format for how the data about the heavy peptides should be stored was established to ensure that the data would be reusable at a later point in time, and also ensures that the heavy peptide data are easily imported to a more permanent system.

\section{Conclusion}

Organizing data in a mutually agreed upon format is crucial as the amount of data increases when researchers collaborate on different experiments. To overcome the challenges that a number of different data formats from a number of different external companies and internal researchers present, PROBE researchers came to the conclusion that a standard format was needed to store and organize their data. The need for a computer system making data available throughout the entire research process, all the way from quality control of the peptides in an upcoming order to the organization of samples, became evident. The aim of this thesis is to provide PROBE with such a computer system.